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---
license: mit
base_model: beomi/KcELECTRA-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: 0322_cosmetic3_kcelectra
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0322_cosmetic3_kcelectra
This model is a fine-tuned version of [beomi/KcELECTRA-base](https://huggingface.co/beomi/KcELECTRA-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3637
- Accuracy: 0.8700
- F1: 0.8703
- Precision: 0.8789
- Recall: 0.8700
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4536 | 1.0 | 277 | 0.3556 | 0.8768 | 0.8734 | 0.8873 | 0.8768 |
| 0.2608 | 2.0 | 554 | 0.5060 | 0.8261 | 0.8252 | 0.8415 | 0.8261 |
| 0.1171 | 3.0 | 831 | 0.5406 | 0.8623 | 0.8571 | 0.8768 | 0.8623 |
| 0.1393 | 4.0 | 1108 | 0.5734 | 0.8768 | 0.8752 | 0.8862 | 0.8768 |
| 0.2115 | 5.0 | 1385 | 0.6661 | 0.8913 | 0.8915 | 0.8924 | 0.8913 |
| 0.0939 | 6.0 | 1662 | 0.5506 | 0.9058 | 0.9054 | 0.9057 | 0.9058 |
| 0.1122 | 7.0 | 1939 | 0.6672 | 0.8986 | 0.8985 | 0.8987 | 0.8986 |
| 0.2413 | 8.0 | 2216 | 0.7136 | 0.8949 | 0.8949 | 0.8950 | 0.8949 |
| 0.001 | 9.0 | 2493 | 0.6689 | 0.9058 | 0.9058 | 0.9058 | 0.9058 |
| 0.0013 | 10.0 | 2770 | 0.6764 | 0.9094 | 0.9094 | 0.9094 | 0.9094 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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